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Economist Charts New Waters With Spatial-Fishing Model

Story posted February 08, 2007

Few problems are as hotly debated in New England — and difficult to resolve — as the state of the fishing industry. Declining fish stocks caused by over-fishing worldwide have given rise to pressing ecological, social, and economic concerns.

Regulatory measures enacted by governments to protect fish stocks — such as catch limits, reduced days at sea, and territorial limits — clearly have not reversed the ecologic and economic downturn of these dwindling resources. Further, they often have dramatically exacerbated the pressures on fishermen and communities fighting for a longstanding way of life.

Assistant Professor Ta Herrera in class.

One of the primary reasons for this disconnect, says Assistant Professor of Economics Guillermo "Ta" Herrera, is that the vested parties — biologists, fishermen, regulators and politicians — are operating with different sets of information.

"Compared to other resources, there is more uncertainty about fish stocks," he says. "Uncertainty about their location, the magnitude and health of their population, their interrelationship with other species. One of my favorite adages is: Fish are like trees, except they are invisible and they move. This, of course, makes them interesting to study."

Herrera has invested much of his career in the study of fish populations and their exploitation, including a recent two-year research sabbatical at the Marine Policy Center of the Woods Hole Oceanographic Institution (WHOI).

Not the average swath for an economist, but a natural trajectory for Herrera, given his background and interests.

"...Fish are like trees, except they are invisible and they move. This, of course, makes them interesting to study."

He began his studies as a biology undergraduate at Harvard. An interest in conservation biology led into graduate studies at the University of Washington in quantitative ecology, and ultimately, economics. "Through all of this, I was interested in the policy implications of what I was doing," says Herrera, who has taught at Bowdoin since 2000. "I wanted to affect things for the better in some way."

His overlapping interests appear to be paying off. With the modeling tools of an economist, and the training of a biologist, Herrera is helping to develop a spatially based economic model for measuring fish stocks and fishing regulations — to better understand the importance of how fish move and where people catch them.

In one such project, Herrera is teaming with WHOI scientist Michael Neubert to develop a spatial model that will create a more realistic picture of the biological, political, and social dimensions of fisheries.

In the standard, textbook model of an exploited fish population, harvesters exert more and more fishing effort until the stock is severely depleted and nobody makes a profit. In order to save the fish and make the industry more profitable, a regulator needs to reduce fishing effort.

Figure 1. The standard non-spatial model shows that an unregulated harvest equilibrates at open access, where no net benefits arise from the resource. To maximize net benefits and increase fish stocks, effort must be reduced to the optimally regulated, at social and political cost.

In the real world, he notes, this means depriving some people of access to the ocean's resources, a political can of worms. "The main reason fisheries regulations are objectionable to many is that they kick people out of industries in which their families have participated for generations," Herrera observes, citing recent cases where fishermen's objections to losing access to the fishery have hindered regulation.

Herrera and Neubert wanted to develop a new model for looking at this old dilemma, so they began exploring the qualitative changes that might occur by considering the movement of fish in space. "Depiction of the spatial reality of fisheries is critical," says Herrera, "as is regulation that is able to dictate where people fish."

They began with a stylized, but plausible, model of a fish stock that both grows and diffuses in space. In their model, fish that move off the edge of the habitat — say, a reef or shelf in the ocean — die and are lost from the system. The natural equilibrium in this model has relatively dense fish population in the middle of the habitat, and a relatively sparse one at the edges.

In the context of this model, Herrera and his colleague asked specific questions: In an unregulated (open-access) setting, how much effort do harvesters exert, and how is this effort distributed in space? And how does this compare to the optimally regulated outcome — a scenario that would yield maximum profits?

"If regulation is crafted with an awareness of the ecological reality of the system, it is indeed possible to achieve a happy coincidence of biological, financial, and social concerns."

"In an unregulated environment, harvesters target places where there are a lot of fish and where it's therefore cheap to catch them," notes Herrera. "It's rational for these fishermen to say, I'll get the most profit per day fishing in the center of the habitat." This pattern of exploitation leads to results similar to that from the simple (non-spatial) model: Severely depleted fish stocks and a meager living for all participants in the industry.

The optimally regulated scenario looks very different, as it is characterized by "prudent predation." Effort is focused at the edges of the habitat, catching fish that are at high risk of being lost off the edge of the habitat. Fish in the center are left to supply the rest of the system with biomass — a marine protected area.

When they combined the two scenarios, Herrera says he and his research partner "thought we would get a spatially structured version of the standard model results. We expected to find that optimal regulation would achieve higher fish stocks and higher profits by pushing some participants out of the industry. End of story."

The story turned out to have quite a surprise ending.

In many cases, their prudent-predation model showed that the total amount of fishing effort allowed by a regulator was actually higher than that exerted in the unregulated scenario. In fact, if spatial regulation is done right, there are triple benefits: more profits in total, a healthier fish stock, and more employment, not less. (See Figure 2.)

Figure 2. In a spatial model, unregulatetd harvest focuses on the center of the habitat, while optimally regulated outcomes fish primarily on the edges. The latter outcome yields higher economic benefits and a larger (healthier) biological resource. In some cases, the total employment in the optimally regulated case, represented by the area under the effort profile, is actually larger than in the unregulated case.

"Highly counterintuitive, qualitative differences emerged that surprised us," says Herrera. "Prevailing wisdom emerging from economic theory is that you can achieve biological and pecuniary objectives through regulation— but that these benefits come hand-in-hand with employment reduction and significant political cost.

"But our results show that if you do a better blend of ecology and economics, you can mitigate, or actually even reverse, that employment effect."

Herrera readily acknowledges the limits of his theory, for instance the logistics and costs of enforcing fine-scale spatially based regulation. But he says it offers strong support for ecologically sophisticated regulation:

"In other versions of our model, we've shown that being able to regulate along dimensions such as fish species, fish size, or even the sex of fish can also take the sting out of regulation in terms of reduced employment.

"The take-home message is that it is important for biologists, economists, and politicians to communicate with one another during the management process," says Herrera. "If regulation is crafted with an awareness of the ecological reality of the system, it is indeed possible to achieve a happy coincidence of biological, financial, and social concerns."